With equipment for cell and tissue preparation, sectioning and labelling.
Established labelling techniques range from various histochemical stainings, immunohistochemistry to multiple fluorescence immunolabellings.
The techniques are used in a wide range of projects, including histopathology assesments, preclinical studies of theraputic drugs and basic research.
Transmitted light, epi-fluoresence wide-field and confocal microscopes
Our platform includes different up-right and inverted microscopes for wide-field analyses and imaging, using bright-field transmitted light and fluorescence.
Our confocal microscop (Zeiss LSM800) is used for high resolution analyses at cellular/intracellular levels, including drug targeting, cellular uptake and treatment effects, in tissue, in vitro and multiwell plates.
The microsope is equiped with near infrared (NIR) detection, a high sensitive detector for low fluorescence signals (GAsp) and allows tiling of tissue specimen or wells at high resolution. The Airyscan detector provides extra high resolution (approximately 130 nm). Images obtained with our microscopes are used for both qualitative and quantitative data analyses.
Cancer cells labelled with a NIR probe are checked with a NIR equipped microscope before inoculation.
Tumor growth is monitored during in vivo experiment.
After the animal is sacrificed the tumor and other organs are harvested and NIR tissue can be detected on a cellular level.
Other fluorescens labelling can be done with complementing markers.
Share scanned images with both overview of whole tissue and of full resolution with pathologist.
Annotations done by the pathologist is saved.
Automatic extraction of annotated regions of interest is fed to the quantitation step for further analysis.
Integrate other experimental and clinical data with the imaging results.
Customize the analysis to project specific needs by using all the available packages the R statistical open source environment.
Combine with image analysis software such as ImageJ, QPath and Orbit to get quality data from images.